• Smart Structures and Systems
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• v.21 no.6
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• pp.727-740
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• 2018

Tuned mass dampers (TMDs) are passive damping devices widely employed to mitigate the pedestrian-induced vibrations on footbridges. The TMD design must ensure an adequate performance during the overall life-cycle of the structure. Although the TMD is initially adjusted to match the natural frequency of the vibration mode which needs to be controlled, its design must further take into account the change of the modal parameters of the footbridge due to the modification of the operational and environmental conditions. For this purpose, a motion-based design optimization method is proposed and implemented herein, aimed at ensuring the adequate behavior of footbridges under uncertainty conditions. The uncertainty associated with the variation of such modal parameters is simulated by a probabilistic approach based on the results of previous research reported in literature. The pedestrian action is modelled according to the recommendations of the Synpex guidelines. A comparison among the TMD parameters obtained considering different design criteria, design requirements and uncertainty levels is performed. To illustrate the proposed approach, a benchmark footbridge is considered. Results show both which is the most adequate design criterion to control the pedestrian-induced vibrations on the footbridge and the influence of the design requirements and the uncertainty level in the final TMD design.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.116-122
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• 2006

Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.402-410
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• 2013

In this paper, a novel and robust Power System Stabilizer (PSS) is proposed as an effective approach to improve stability in electric power systems. The dynamic performance of proposed PSS has been thoroughly compared with Conventional PSS (CPSS). Both the Real Coded Genetic Algorithm (RCGA) and Particle Swarm Optimization (PSO) techniques are applied to optimum tune the parameter of both the proposed PSS and CPSS in order to damp-out power system oscillations. Due to the high sufficiency of both the RCGA and PSO techniques to solve the very non-linear objective, they have been employed for solution of the optimization problem. In order to verify the dynamic performance of these devices, different conditions of disturbance are taken into account in Single Machine Infinite Bus (SMIB) power system. Moreover, to ensure the robustness of proposed PSS in damping the power system multi-mode oscillations, a Multi Machine (MM) power system under various disturbances are considered as a test system. The results of nonlinear simulation strongly suggest that the proposed PSS significantly enhances the power system dynamic stability in both of the SMIB and MM power system as compared to CPSS.

• Computational Structural Engineering
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• v.9 no.3
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• pp.179-186
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• 1996

A simple nonlinear programming(NLP) formulation for the optimal topology problem of structures is developed and examined. The NLP formulation is general, and can handle arbitrary objective functions and arbitrary stress, displacement constraints under multiple loading conditions. The formulation is based on simultaneous analysis and design approach to avoid stiffness matrix singularity resulting from zero sizing variables. By embedding the equilibrium equations as equality constraints in the nonlinear programming problem, we avoid constructing and factoring a system stiffness matrix, and hence avoid its singularity. The examples demonstrate that the formulation is effective for finding an optimal solution, and shown to be robust under a variety of constraints.

• Journal of Information Technology Services
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• v.19 no.2
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• pp.109-124
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• 2020

Facing the 4^th Industrial Revolution era, researches on artificial intelligence have become active and attempts have been made to apply machine learning in various fields. In the field of finance, Robo Advisor service, which analyze the market, make investment decisions and allocate assets instead of people, are rapidly expanding. The stock price prediction using the machine learning that has been carried out to date is mainly based on the prediction of the market index such as KOSPI, and utilizes technical data that is fundamental index or price derivative index using financial statement. However, most researches have proceeded without any explicit verification of the prediction rate of the learning data. In this study, we conducted an experiment to determine the degree of market prediction ability of basic indicators, technical indicators, and system risk indicators (AR) used in stock price prediction. First, we set the core parameters for each financial indicator and define the objective function reflecting the return and volatility. Then, an experiment was performed to extract the sample from the distribution of each parameter by the Markov chain Monte Carlo (MCMC) method and to find the optimum value to maximize the objective function. Since Robo Advisor is a commodity that trades financial instruments such as stocks and funds, it can not be utilized only by forecasting the market index. The sample for this experiment is data of 17 years of 1,500 stocks that have been listed in Korea for more than 5 years after listing. As a result of the experiment, it was possible to establish a meaningful trading strategy that exceeds the market return. This study can be utilized as a basis for the development of Robo Advisor products in that it includes a large proportion of listed stocks in Korea, rather than an experiment on a single index, and verifies market predictability of various financial indicators.

• Journal of Korea Water Resources Association
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• v.52 no.4
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• pp.291-300
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• 2019

If pipes are damaged in a water distribution network (WDN), adjacent valves are closed to isolate the pipes for repair. Due to the closed valves, parts of WDN are isolated from water supply sources. The isolated area is divided into Intended Isolation Area (IIA) and Unintended Isolation Area (UIA). The IIA occurs by intention to isolate the damaged pipe, while UIA is unintentionally disconnected from the sources due to IIA. Thus, the extension of isolated area and suspended flows are mainly affected by number and location of installed valves in WDN. In this study, optimization models were developed to determine optimal valve locations in WDN. In a single-objective model, total water supply suspension is minimized, while a multi-objective model intends to simultaneously minimize the suspended flow and valve installation cost. Optimal valve placement results obtained from both models were compared and analyzed using a sample application network.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.129-139
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• 2016

This paper presented a robust ship scheduling model using the quadratic programming problem. Given a set of available carriers under control and a set of cargoes to be transported from origin to destination, a robust ship scheduling that can minimize the mean-variance objective function with the required level of profit can be modeled. Computational experiments concerning relevant maritime transportation problems are performed on randomly generated configurations of tanker scheduling in bulk trade. In the first stage, the optimal transportation problem to achieve maximum revenue is solved through the traditional set-packing model that includes all feasible schedules for each carrier. In the second stage, the robust ship scheduling problem is formulated as mentioned in the quadratic programming. Single index model is used to efficiently calculate the variance-covariance matrix of objective function. Significant results are reported to validate that the proposed model can be utilized in the decision problem of ship scheduling after considering robustness and the required level of profit.

• Journal of Animal Reproduction and Biotechnology
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• v.37 no.4
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• pp.226-230
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• 2022

The sheep can be reproduced by natural mating as well as applied reproductive biotechnology, embryo transfer (ET). However, this method in sheep is influenced by several factors such as season, photoperiod, latitude, temperature, nutrition, and breed. In addition, there is still less research on assisted reproductive technologies in small ruminants, compared to other livestock species such as cattle and pigs. Because there has been a need for an optimization and a continuous improvement of ET techniques in small ruminants. the main objective of this study was to evaluate the conception rate obtained after ET in Mongolian sheep (Dorper breed). After embryo recover, code 1 and 2 embryos (morula or blastocyst stage) for ET in the present study were 63% (63/100) and 24% (24/100), respectively. Then Each single embryo was transferred to a synchronized recipient who prepared by estrous synchronization protocol with fluorogestone acetate-cloprostenol sodium. The results demonstrated that an average conception rate and lambing rate was 35.6% (31/87) and 33.3% (29/87), respectively. Further study is still necessary, but these results indicated that single embryo of Mongolian sheep with the present protocol was enough to conducting ET when the genetically superior sheep were necessary to be expanded.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.217-229
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• 2007

In this paper, Genetic Algorithm (GA) is used to find the Maximum Weight Independent Set (MWIS) of a graph. First, MWIS problem is formulated as a 0-1 integer programming optimization problem with linear objective function and a single quadratic constraint. Then GA is implemented with the help of this formulation. Since GA is a heuristic search method, exact solution is not reached in every run. Though the suboptimal solution obtained is very near to the exact one. Computational result comprising an average performance is also presented here.

• Journal of Korean Society for Quality Management
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• v.28 no.1
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• pp.78-94
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• 2000

The ever increasing demands for enhanced competitiveness of engineered products require a "designing-in-quality" strategy that can effectively and efficiently incorporate concepts of uncertainty, quality, and robustness into design. Engineered design optimization approaches that are typically carried out with respect to a single objective become inadequate to address these multiple set of requirements. This paper presents a design metric for a multi-attribute robust design problem with designer′s preferences on the performance accuracy and the performance precision. The use of this design metric as the robust optimal design criterion in multi-stage experimentation and modeling technique is presented. The effectiveness of the overall design procedure and the performance of the proposed design metric are tested with the aid of IC design and the results are discussed.